agent-browser

What this skill does

# agent-browser: CLI Browser Automation

Vercel's headless browser CLI designed for AI agents. Uses ref-based selection (@e1, @e2) from accessibility snapshots.

## Setup Check

```bash
command -v agent-browser >/dev/null 2>&1 && echo "Installed" || echo "NOT INSTALLED"
```

### Install if needed

```bash
npm install -g agent-browser
agent-browser install  # Downloads Chromium
```

## Core Workflow

**The snapshot + ref pattern is optimal for LLMs:**

1. **Navigate** to URL
2. **Snapshot** to get interactive elements with refs
3. **Interact** using refs (@e1, @e2, etc.)
4. **Re-snapshot** after navigation or DOM changes

```bash
# Step 1: Open URL
agent-browser open https://example.com

# Step 2: Get interactive elements with refs
agent-browser snapshot -i

# Step 3: Interact using refs
agent-browser click @e1
agent-browser fill @e2 "search query"

# Step 4: Re-snapshot after changes
agent-browser snapshot -i
```

## Key Commands

### Navigation

```bash
agent-browser open <url>       # Navigate to URL
agent-browser back             # Go back
agent-browser forward          # Go forward
agent-browser reload           # Reload page
agent-browser close            # Close browser
```

### Snapshots (Essential for AI)

```bash
agent-browser snapshot              # Full accessibility tree
agent-browser snapshot -i           # Interactive elements only (recommended)
agent-browser snapshot -i --json    # JSON output for parsing
agent-browser snapshot -c           # Compact (remove empty elements)
agent-browser snapshot -d 3         # Limit depth
agent-browser snapshot -s @e5       # Scope to element subtree
```

### Interactions

```bash
agent-browser click @e1                    # Click element
agent-browser dblclick @e1                 # Double-click
agent-browser fill @e1 "text"              # Clear and fill input
agent-browser type @e1 "text"              # Type without clearing
agent-browser press Enter                  # Press key
agent-browser hover @e1                    # Hover element
agent-browser check @e1                    # Check checkbox
agent-browser uncheck @e1                  # Uncheck checkbox
agent-browser select @e1 "option"          # Select dropdown option
agent-browser scroll down 500              # Scroll (up/down/left/right)
agent-browser scrollintoview @e1           # Scroll element into view
```

### Get Information

```bash
agent-browser get text @e1          # Get element text
agent-browser get html @e1          # Get element HTML
agent-browser get value @e1         # Get input value
agent-browser get attr href @e1     # Get attribute
agent-browser get title             # Get page title
agent-browser get url               # Get current URL
agent-browser get count "button"    # Count matching elements
```

### Screenshots & PDFs

```bash
agent-browser screenshot                      # Viewport screenshot
agent-browser screenshot --full               # Full page
agent-browser screenshot output.png           # Save to file
agent-browser pdf output.pdf                  # Save as PDF
```

### Wait

```bash
agent-browser wait @e1              # Wait for element
agent-browser wait 2000             # Wait milliseconds
agent-browser wait "text"           # Wait for text to appear
agent-browser wait --url "pattern"  # Wait for URL match
```

## Semantic Locators (Alternative to Refs)

```bash
agent-browser find role button click --name "Submit"
agent-browser find text "Sign up" click
agent-browser find label "Email" fill "[email protected]"
agent-browser find placeholder "Search..." fill "query"
```

## Sessions & Profiles

### Sessions (Parallel Isolated Browsers)

```bash
agent-browser --session browser1 open https://site1.com
agent-browser --session browser2 open https://site2.com
agent-browser session list
```

### Profiles (Persistent State Across Restarts)

```bash
# Profiles preserve cookies, localStorage, login sessions
agent-browser --profile ~/.myapp-profile open https://app.example.com
```

## Authentication

### Skip UI Login with Headers

```bash
agent-browser open https://api.example.com --headers '{"Authorization": "Bearer <token>"}'
```

### Save/Load Auth State

```bash
# After logging in via UI
agent-browser state save auth-state.json

# Reuse in future sessions
agent-browser state load auth-state.json
agent-browser open https://app.example.com  # Already logged in
```

## Debug Mode

```bash
# Run with visible browser window
agent-browser --headed open https://example.com
agent-browser --headed snapshot -i
agent-browser --headed click @e1
```

## Examples

### Login Flow

```bash
agent-browser open https://app.example.com/login
agent-browser snapshot -i
# Output: textbox "Email" [ref=e1], textbox "Password" [ref=e2], button "Sign in" [ref=e3]
agent-browser fill @e1 "[email protected]"
agent-browser fill @e2 "password123"
agent-browser click @e3
agent-browser wait 2000
agent-browser snapshot -i  # Verify logged in
```

### Search and Extract

```bash
agent-browser open https://news.ycombinator.com
agent-browser snapshot -i
agent-browser get text @e12  # Get headline text
agent-browser click @e12     # Click to open story
```

### Form Filling

```bash
agent-browser open https://forms.example.com
agent-browser snapshot -i
agent-browser fill @e1 "John Doe"
agent-browser fill @e2 "[email protected]"
agent-browser select @e3 "United States"
agent-browser check @e4  # Agree to terms
agent-browser click @e5  # Submit
agent-browser screenshot confirmation.png
```

## JSON Output

```bash
agent-browser snapshot -i --json
```

Returns structured data with refs for programmatic parsing.

## vs Playwright MCP

| Feature | agent-browser (CLI) | Playwright MCP |
|---------|---------------------|----------------|
| Interface | Bash commands | MCP tools |
| Selection | Refs (@e1) | Refs (e1) |
| Output | Text/JSON | Tool responses |
| Parallel | Sessions | Tabs |
| Best for | Quick automation | Tool integration |

**Use agent-browser when:**
- You prefer Bash-based workflows
- You want simpler CLI commands
- You need quick one-off automation

**Use Playwright MCP when:**
- You need deep MCP tool integration
- You want tool-based responses
- You're building complex automation